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StarTree Cloud vs. ClickHouse Cloud: Which real-time OLAP platform is right for you?
Users are increasingly turning to a new generation of databases designed for the demands of real-time Online Analytical Processing (OLAP). When it comes to StarTree Cloud vs. ClickHouse Cloud, which one is right for your use case?
9 Reasons to choose StarTree Cloud over ClickHouse Cloud
High Queries Per Second (QPS)
Unlock your data for internal & external users by supporting extremely high concurrency queries (100,000+ QPS).
Scalable Upserts
StarTree does upserts right. Done at ingestion time, not query time. Scalable. Performant. Full row, partial (per column), and soft deletes.
Fast & Flexible Indexing
Leverage multiple indexing options, including the star-tree index for fast and efficient query results.
Low-Latency Aggregations at Scale
Maintain performant aggregations against petabytes of data, with latencies measured in milliseconds.
Better Tiered Storage
Get results in seconds with tiered storage designed for fast analytics. Query data within milliseconds of ingestion to ensure results are accurate and up to date.
Scalable Joins
Supports performant distributed query-time JOINs across data with a multi-stage query engine.
Multi-Tenancy Design
Isolate tables to only the users that need access to critical data.
Data Management
StarTree includes tools to help onboard data easily, plus manage data backfills and schema changes.
Anomaly Detection
StarTree ThirdEye provides anomaly detection and root-cause analysis for real-time data fluctuations.
Designed for User-Facing Analytics
StarTree Cloud, Powered by Apache Pinot
StarTree Cloud is powered by Apache Pinot, a free open-source software (FOSS) database designed for real-time analytics. ClickHouse Cloud is powered by ClickHouse, another FOSS database designed for real-time analytics. Yet not all real-time analytical databases are designed the same.
Learn more: An In-Depth Comparison of Apache Pinot, Apache Druid and ClickHouse
Apache Pinot is capable of supporting a high rate of queries per second (QPS) with low latencies — often as low as single digit millisecond or submillisecond results. Apache Pinot can perform fast ingestion and produce fresh results against massive datasets in the terabytes to petabytes scale while still maintaining high query concurrency.
While Apache Pinot and ClickHouse share many architectural similarities, it is in scalability where their specific differences become immediately apparent. While ClickHouse can also support low latency queries, these low latencies are only if users keep queries simple, with comparatively low throughput / concurrency. ClickHouse also has issues with scaling upserts.
Meanwhile Apache Pinot users, like Stripe, can easily run 10,000 QPS or more. Apache Pinot can thus support user-facing analytics, where high concurrency of queries is a strict requirement. On top of that, StarTree Cloud has infrastructure to support billions of upserts.
Real User Stories
Cisco WebEx needed to scale to meet the needs of explosive growth of video conferencing. To test their workloads, they took 30 billion rows of data and set up a comparison of Apache Pinot vs. ClickHouse. They found Apache Pinot had clear advantages in three ways over ClickHouse:
- Performance: Unlike ClickHouse, Pinot was able to maintain exceptionally low p99 latencies, even at higher concurrencies. For more complex queries ClickHouse latencies increased precipitously to nearly 30 seconds, even for 5 to 20 QPS. Pinot ran faster in 5 of 6 query types, comparably in 1, and for 3 of 6 query types it actually ran more than 4x faster than ClickHouse. Overall, Pinot’s throughput was 40% higher than that of ClickHouse.
- Ease of Operations: The Webex team found Pinot somewhat more involved to set up, but once deployed, Pinot was natively much easier to use, with simple cluster management, quality of service, and plenty of automation — whereas ClickHouse required far more manual configuration and did not support multi-tenancy or tiered storage. Note that this requirement is made even easier with StarTree Cloud, a fully-managed service powered by Apache Pinot that enhances performance and expands tiered storage capabilities even more.
- Extensibility: Because both Pinot and ClickHouse are relatively new solutions, Webex wanted to ensure extensibility to potential new use cases. Here, too, they preferred Pinot, which is written in Java, rather than ClickHouse, written in the more complex C++.
Comparing performance: StarTree wins hands-down
Cisco Webex
Cisco Webex found Apache Pinot provided 4x lower query latency than ClickHouse, especially at higher concurrencies. (Lower results are better.)
With Apache Pinot, Cisco Webex was able to drive 40% more queries per second (QPS), providing higher throughput on the same infrastructure.
YouGov
YouGov tried various databases to meet their needs for fast analytics. This found a clear advantage of using a real-time Online Analytical Processing (OLAP) database compared to traditional Online Transactional Processing (OTLP) databases like PostgreSQL (SQL) or Cassandra (NoSQL).
Even amongst real-time OLAP databases Apache Pinot handily out-performed Apache Druid and Clickhouse. YouGov found Pinot to be up to 7x faster than ClickHouse. (Lower results are better.)
Advantages of StarTree Cloud
Compare the features of StarTree Cloud, powered by Apache Pinot, to ClickHouse Cloud and you’ll see that StarTree offers far more flexible indexing capabilities to perform real-time analytics.
StarTree Cloud
ClickHouse Cloud
Multi-Tenancy
Cluster Operations
Data Backfilling
Schema Evolution
Security
Role-Based Access Control (RBAC)
Encryption (Data-at-Rest)
Encryption (Data-in-Transit)
SQL
Query-Time JOINs
Window Functions
User Defined Functions (UDFs)
UDFs Using Custom JAR
Query Caching
Automated Query Performance Optimization
Indexing Strategies
Inverted Index
Sorted Index
Range Index
JSON Index
Geospatial Index
Star-Tree Index
Bloom Filter
Text Index
Timestamp Index
Sparse Index
Ingestion
Change Data Capture (CDC)
Real-Time Deduplication
Pauseless Ingestion
Native Kafka Support
Real-Time Ingestion Scalability
Out-of-Order Handling
Upserts (Full-Row, Partial-Row)
Scalable Upserts
Exactly-Once Ingestion Guarantee
Event Streaming Ingestion
Apache Kafka
Amazon Kinesis
Apache Pulsar
Google PubSub
Object Store Support (Batch Ingestion)
Amazon S3
Google Cloud Storage (GCS)
Azure Data Lake Storage (ADLS) gen2
Hadoop Distributed File System (HDFS)
Batch Ingestion File Formats
Arrow
Avro
CSV
FlattenSpec
JSON
ORC
Parquet
Protocol Buffers (Profobuf)
Thrift
TSV
Data Analytics Integration
Apache Spark
Tiered Storage
Multi-Volume Tiering
Compute Node Separation
Cloud Object Storage
Visualization
Apache Superset
Tableau
Looker Studio
Grafana
Embeddable
Ready to take StarTree Cloud for a spin?
Start a free trial or meet with our experts. Discover how easy it is to get started migrating your workloads to Apache Pinot with StarTree Cloud.